Title: Research on pipe crack detection based on image processing algorithm

Authors: Licheng Huang; Bo Tao; Donghai Chen; Xun Zhang; Gongfa Li

Addresses: Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan, Hubei, China ' Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan, Hubei, China ' Changjiang Survey, Planning, Design and Research Limited Company, Wuhan, Hubei, China ' Changjiang Survey, Planning, Design and Research Limited Company, Wuhan, Hubei, China ' Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan, Hubei, China

Abstract: Pipe cracks detection based on machine vision is a new and effective technology. However, it requires high quality of the image. Moreover, images with adequate lighting, evident cracks, clean backgrounds are difficult to obtain in practice. This paper proposes an algorithm for pipe cracks detection in natural background. The algorithm performs filtering, background segmentation, edge detection, threshold segmentation, morphological contour extraction and annotation on the image. This paper also proposes an adaptive threshold segmentation method to obtain the clear crack. By comparing the proposed algorithm with the DEE algorithm, the result shows that the proposed algorithm has certain advantages in experiments. The experiment results show that the algorithm proposed can be used in significant pipe cracks detection.

Keywords: pipe cracks; noise reduce; Sobel operator; edge detection; image processing.

DOI: 10.1504/IJWMC.2021.117550

International Journal of Wireless and Mobile Computing, 2021 Vol.20 No.4, pp.328 - 335

Received: 24 Aug 2020
Accepted: 14 Sep 2020

Published online: 02 Sep 2021 *

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